A Dataproc job for running Apache Spark applications on YARN.
JSON representation |
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{ "args": [ string ], "jarFileUris": [ string ], "fileUris": [ string ], "archiveUris": [ string ], "properties": { string: string, ... }, "loggingConfig": { object ( |
Fields | |
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args[] |
Optional. The arguments to pass to the driver. Do not include arguments, such as |
jar |
Optional. HCFS URIs of jar files to add to the CLASSPATHs of the Spark driver and tasks. |
file |
Optional. HCFS URIs of files to be placed in the working directory of each executor. Useful for naively parallel tasks. |
archive |
Optional. HCFS URIs of archives to be extracted into the working directory of each executor. Supported file types: .jar, .tar, .tar.gz, .tgz, and .zip. |
properties |
Optional. A mapping of property names to values, used to configure Spark. Properties that conflict with values set by the Dataproc API might be overwritten. Can include properties set in /etc/spark/conf/spark-defaults.conf and classes in user code. An object containing a list of |
logging |
Optional. The runtime log config for job execution. |
Union field driver . Required. The specification of the main method to call to drive the job. Specify either the jar file that contains the main class or the main class name. To pass both a main jar and a main class in that jar, add the jar to jarFileUris , and then specify the main class name in mainClass . driver can be only one of the following: |
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main |
The HCFS URI of the jar file that contains the main class. |
main |
The name of the driver's main class. The jar file that contains the class must be in the default CLASSPATH or specified in SparkJob.jar_file_uris. |